Cisco
CompTIA
ISC
EC-Council
EXIN
Fortinet
ITIL
Juniper
Microsoft
VMware
Avaya
SAP
Google
NVIDIA
Salesforce
Amazon
Palo Alto Networks
ISC2
Splunk
ServiceNow
All Vendors
  2. Home
  3. Exams
  4. NVIDIA
  5. NCP-AAI

NVIDIA NCP-AAI Exam
Agentic AI (Page 3 )

Updated On: 7-Feb-2026
Page 3 of 26
PDF with 121 Questions

When implementing inter-agent communication for a distributed agentic system running across multiple NVIDIA GPU nodes, which message routing pattern provides the best balance of reliability and performance?

  1. Database-based message queuing with polling
  2. Direct TCP connections between all agent pairs
  3. Event-driven message routing with distributed broker clusters
  4. Centralized message broker with topic-based routing

Answer(s): C

Explanation:

An event-driven routing pattern using distributed broker clusters provides scalable, fault-tolerant communication with low latency. It supports high-throughput inter-agent messaging across GPU nodes while avoiding the bottlenecks and fragility of centralized brokers or direct peer-to-peer connections.



Which two orchestration methods are MOST suitable for implementing complex agentic workflows that require both external data access and specialized task delegation? (Choose two.)

  1. Agentic orchestration with specialized expert system delegation
  2. Prompt chaining to accomplish state management
  3. Manual workflow coordination without automation
  4. Retrieval-based orchestration for external data
  5. Static rule-based routing with predefined pathways

Answer(s): A,D

Explanation:

Expert system delegation enables agents to route tasks to specialized components for complex reasoning, while retrieval-based orchestration provides structured access to external knowledge sources. Together, these methods support sophisticated workflows requiring both dynamic task delegation and real-time data integration.



When evaluating coordination failures in a multi-agent system managing distributed manufacturing workflows, which analysis approach best identifies state management and planning synchronization issues?

  1. Monitor agent outputs individually to confirm local correctness and examine results of specific workflow steps.
  2. Deploy distributed state tracing across agents, analyze transition timing, study communication overhead, and verify synchronization accuracy.
  3. Assess synchronization methods during design reviews and use simulations to evaluate coordination across representative workflow scenarios.
  4. Track workflow throughput and task completions to measure performance trends and highlight workflow outcomes.

Answer(s): B

Explanation:

Distributed state tracing reveals how agents exchange state, synchronize plans, and transition between workflow steps. Analyzing timing and communication overhead exposes where coordination breaks down, making it the most effective method for diagnosing multi-agent synchronization failures.



You are designing an AI agent for summarizing medical documents that include images and text as well. It must extract key information and recognize dates.

Which feature is most critical for ensuring the agent performs well across multiple input and output formats?

  1. Use of guardrails to filter out hallucinated content
  2. Retry logic implementation to ensure robustness during API failures
  3. Chain-of-thought prompting for reasoning accuracy
  4. Multi-modal model integration to handle both text and vision inputs

Answer(s): D

Explanation:

Handling both the textual content and embedded images (for things like dates in scans or charts) requires a multimodal model that can jointly process vision and text. This enables the agent to consistently extract key information and recognize dates regardless of whether they appear in written text, tables, or visual elements.



Which two coordination patterns are MOST effective for implementing a multi-agent system where agents have different specializations (Research Analyst, Content Writer, Quality Validator)?

  1. Sequential pipeline coordination with crew-based structured handoffs
  2. Peer-to-peer coordination with consensus mechanisms
  3. Random task distribution with load balancing
  4. Hierarchical coordination with crew-based task delegation

Answer(s): A,D

Explanation:

Sequential pipeline coordination enables each specialized agent to contribute in a structured handoff, matching the natural flow of research writing validation. Hierarchical coordination with task delegation further ensures that specialized agents receive tasks aligned to their expertise while maintaining overall workflow control, producing consistent and optimized multi-agent collaboration.



Viewing page 3 of 26
Viewing questions 11 - 15 out of 121 questions



Post your Comments and Discuss NVIDIA NCP-AAI exam prep with other Community members:

Join the NCP-AAI Discussion